OpenRaiser/Intern-Atlas huggingface dataset:
Multilayer Network of Language: a Unified Framework for Structural Analysis of Linguistic Subsystems
Venue: arXiv cs.CL 2015
Year: 2015

Recently, the focus of complex networks research has shifted from the analysis of isolated properties of a system toward a more realistic modeling of multiple phenomena - multilayer networks. Motivated by the prosperity of multilayer approach in social, transport or trade systems, we propose the introduction of multilayer networks for language. The multilayer network of language is a unified framework for modeling linguistic subsystems and their structural properties enabling the exploration of their mutual interactions. Various aspects of natural language systems can be represented as complex networks, whose vertices depict linguistic units, while links model their relations. The multilayer network of language is defined by three aspects: the network construction principle, the linguistic subsystem and the language of interest. More precisely, we construct a word-level (syntax, co-occurrence and its shuffled counterpart) and a subword level (syllables and graphemes) network layers, from five variations of original text (in the modeled language). The obtained results suggest that there are substantial differences between the networks structures of different language subsystems, which are hidden during the exploration of an isolated layer. The word-level layers share structural properties regardless of the language (e.g. Croatian or English), while the syllabic subword level expresses more language dependent structural properties. The preserved weighted overlap quantifies the similarity of word-level layers in weighted and directed networks. Moreover, the analysis of motifs reveals a close topological structure of the syntactic and syllabic layers for both languages. The findings corroborate that the multilayer network framework is a powerful, consistent and systematic approach to model several linguistic subsystems simultaneously and hence to provide a more unified view on language.
Collaborative peer production as an alternative to hierarchical internet based business systems
Venue: arXiv cs.CY 2015
Year: 2015

As we move towards more data intensive, device centric global communication networks, our ability to usefully harvest these large datastores is degrading. The widening asymmetry in the explosive growth of data versus our ability to use it, is forcing us towards centralized analytics. This splintered concentration of data further consolidates analytical capabilities in the hands of the few and divides the network into the analysors and the analysed. The fracturing of the system into opaque datastores and analytics blocks creates a strong positive feedback loop and has a significant negative impact on the stability, transparency and freedom of the network. This paper attempted to identify problems associated with the internet, internet dependent business models and reviewing available solutions and discuss possible solutions which became necessary.
HMIoT: A New Healthcare Model Based on Internet of Things
Venue: arXiv cs.CY 2015
Year: 2015

In recent century, with developing of equipment, using of the internet and things connected to the internet is growing. Therefore, the need for informing in the process of expanding the scope of its application is very necessary and important. These days, using intelligent and autonomous devices in our daily lives has become commonplace and the Internet is the most important part of the relationship between these tools and even at close distances also. Things connected to the Internet that are currently in use and can be inclusive of all the sciences as a step to develop and coordinate of them. In this paper we investigate application and using of Internet of things from the perspective of various sciences. We show that how this phenomenon can influence on future health of people.
Normal forms for linear displacement context-free grammars
Venue: arXiv cs.FL 2015
Year: 2015

In this paper we prove several results on normal forms for linear displacement context-free grammars. The results themselves are rather simple and use well-known techniques, but they are extensively used in more complex constructions. Therefore this article mostly serves educational and referential purposes.
Android Tapjacking Vulnerability
Venue: arXiv cs.CR 2015
Year: 2015

Android is an open source mobile operating system that is developed mainly by Google. It is used on a significant portion of mobile devices worldwide. In this paper, I will be looking at an attack commonly known as tapjacking. I will be taking the attack apart and walking through each individual step required to implement the attack. I will then explore the various payload options available to an attacker. Lastly, I will touch on the feasibility of the attack as well as mitigation strategies.
The Common HOL Platform
Venue: arXiv cs.LO 2015
Year: 2015

The Common HOL project aims to facilitate porting source code and proofs between members of the HOL family of theorem provers. At the heart of the project is the Common HOL Platform, which defines a standard HOL theory and API that aims to be compatible with all HOL systems. So far, HOL Light and hol90 have been adapted for conformance, and HOL Zero was originally developed to conform. In this paper we provide motivation for a platform, give an overview of the Common HOL Platform's theory and API components, and show how to adapt legacy systems. We also report on the platform's successful application in the hand-translation of a few thousand lines of source code from HOL Light to HOL Zero.
Checking Zenon Modulo Proofs in Dedukti
Venue: arXiv cs.LO 2015
Year: 2015

Dedukti has been proposed as a universal proof checker. It is a logical framework based on the lambda Pi calculus modulo that is used as a backend to verify proofs coming from theorem provers, especially those implementing some form of rewriting. We present a shallow embedding into Dedukti of proofs produced by Zenon Modulo, an extension of the tableau-based first-order theorem prover Zenon to deduction modulo and typing. Zenon Modulo is applied to the verification of programs in both academic and industrial projects. The purpose of our embedding is to increase the confidence in automatically generated proofs by separating untrusted proof search from trusted proof verification.
A cubic vertex kernel for Diamond-free Edge Deletion and more
Venue: arXiv cs.DS 2015
Year: 2015

A diamond is a graph obtained by removing an edge from a complete graph on four vertices. A graph is diamond-free if it does not contain an induced diamond. The Diamond-free Edge Deletion problem asks whether there exist at most $k$ edges in the input graph $G$ whose deletion results in a diamond-free graph. For this problem, a polynomial kernel of $O(k^4$) vertices was found by Fellows et. al. (Discrete Optimization, 2011). In this paper, we give an improved kernel of $O(k^3)$ vertices for Diamond-free Edge Deletion. Further, we give an $O(k^2)$ vertex kernel for a related problem {Diamond,K_t}-free Edge Deletion, where $t\geq 4$ is any fixed integer. To complement our results, we prove that these problems are NP-complete even for $K_4$-free graphs and can be solved neither in subexponential time (i.e., $2^{o(|G|)}$) nor in parameterized subexponential time (i.e., $2^{o(k)}\cdot |G|^{O(1)}$), unless Exponential Time Hypothesis fails. Our reduction implies the hardness and lower bound for a general class of problems, where these problems come as a special case.
A System Architecture for Software-Defined Industrial Internet of Things
Venue: arXiv cs.NI 2015
Year: 2015

Wireless sensor networks have been a driving force of the Industrial Internet of Things (IIoT) advancement in the process control and manufacturing industry. The emergence of IIoT opens great potential for the ubiquitous field device connectivity and manageability with an integrated and standardized architecture from low-level device operations to high-level data-centric application interactions. This technological development requires software definability in the key architectural elements of IIoT, including wireless field devices, IIoT gateways, network infrastructure, and IIoT sensor cloud services. In this paper, a novel software-defined IIoT (SD-IIoT) is proposed in order to solve essential challenges in a holistic IIoT system, such as reliability, security, timeliness scalability, and quality of service (QoS). A new IIoT system architecture is proposed based on the latest networking technologies such as WirelessHART, WebSocket, IETF constrained application protocol (CoAP) and software-defined networking (SDN). A new scheme based on CoAP and SDN is proposed to solve the QoS issues. Computer experiments in a case study are implemented to show the effectiveness of the proposed system architecture.
L-Visibility Drawings of IC-planar Graphs
Venue: arXiv cs.CG 2015
Year: 2015

An IC-plane graph is a topological graph where every edge is crossed at most once and no two crossed edges share a vertex. We show that every IC-plane graph has a visibility drawing where every vertex is an L-shape, and every edge is either a horizontal or vertical segment. As a byproduct of our drawing technique, we prove that an IC-plane graph has a RAC drawing in quadratic area with at most two bends per edge.
Service Dependability with Continuously Revised Assurance Cases by Multiple Stakeholders: A Case Study
Venue: arXiv cs.SE 2015
Year: 2015

Recently, assurance cases have received much attentions in the field of software-based computer systems and IT services. However, software very often changes and there are no strong regulations for software. These facts are main two challenges to be addressed in software assurance cases. We propose a development method of assurance cases by means of continuous revision at every stage of the system lifecycle, including in-operation and service recovery in failure cases. The quality of dependability arguments are improved by multiple stakeholders who check with each other. This paper reported our experience of the proposed method in a case of the ASPEN education service. The case study demonstrate that the continuos updates create a significant amount of active risk communications between stakeholders. This gives us a promising perspective for the long-term improvement of service dependability with the lifecycle assurance cases.
Zero and negative energy dissipation at information-theoretic erasure
Venue: arXiv cs.ET 2015
Year: 2015

We introduce information-theoretic erasure based on Shannon's binary channel formula. It is pointed out that this type of erasure is a natural energy-dissipation-free way in which information is lost in double-potential-well memories, and it may be the reason why the brain can forget things effortlessly. We also demonstrate a new non-volatile, charge-based memory scheme wherein the erasure can be associated with even negative energy dissipation; this implies that the memory's environment is cooled during information erasure and contradicts Landauer's principle of erasure dissipation. On the other hand, writing new information into the memory always requires positive energy dissipation in our schemes. Finally, we show a simple system where even a classical erasure process yields negative energy dissipation of arbitrarily large energy.
A Simple Proof for the Optimality of Randomized Posterior Matching
Venue: arXiv cs.IT 2015
Year: 2015

Posterior matching (PM) is a sequential horizon-free feedback communication scheme introduced by the authors, who also provided a rather involved optimality proof showing it achieves capacity for a large class of memoryless channels. Naghshvar et al considered a non-sequential variation of PM with a fixed number of messages and a random decision-time, and gave a simpler proof establishing its optimality via a novel Shannon-Jensen divergence argument. Another simpler optimality proof was given by Li and El Gamal, who considered a fixed-rate fixed block-length variation of PM with an additional randomization. Both these works also provided error exponent bounds. However, their simpler achievability proofs apply only to discrete memoryless channels, and are restricted to a non-sequential setup with a fixed number of messages. In this paper, we provide a short and transparent proof for the optimality of the fully sequential horizon-free PM scheme over general memoryless channels. Borrowing the key randomization idea of Li and El Gamal, our proof is based on analyzing the random walk behavior of the shrinking posterior intervals induced by a reversed iterated function system (RIFS) decoder.
Analysis of Financial News with NewsStream
Venue: arXiv cs.IR 2015
Year: 2015

Unstructured data, such as news and blogs, can provide valuable insights into the financial world. We present the NewsStream portal, an intuitive and easy-to-use tool for news analytics, which supports interactive querying and visualizations of the documents at different levels of detail. It relies on a scalable architecture for real-time processing of a continuous stream of textual data, which incorporates data acquisition, cleaning, natural-language preprocessing and semantic annotation components. It has been running for over two years and collected over 18 million news articles and blog posts. The NewsStream portal can be used to answer the questions when, how often, in what context, and with what sentiment was a financial entity or term mentioned in a continuous stream of news and blogs, and therefore providing a complement to news aggregators. We illustrate some features of our system in three use cases: relations between the rating agencies and the PIIGS countries, reflection of financial news on credit default swap (CDS) prices, the emergence of the Bitcoin digital currency, and visualizing how the world is connected through news.
Calibrating Function Points Using Neuro-Fuzzy Technique
Venue: arXiv cs.SE 2015
Year: 2015

The concepts of calibrating Function Points are discussed, whose aims are to fit specific software application, to reflect software industry trend, and to improve cost estimation. Neuro-Fuzzy is a technique which incorporates the learning ability from neural network and the ability to capture human knowledge from fuzzy logic. The empirical validation using ISBSG data repository Release 8 shows a 22% improvement in software effort estimation after calibration using Neuro-Fuzzy technique.
Towards Distortion-Predictable Embedding of Neural Networks
Venue: arXiv cs.CV 2015
Year: 2015

Current research in Computer Vision has shown that Convolutional Neural Networks (CNN) give state-of-the-art performance in many classification tasks and Computer Vision problems. The embedding of CNN, which is the internal representation produced by the last layer, can indirectly learn topological and relational properties. Moreover, by using a suitable loss function, CNN models can learn invariance to a wide range of non-linear distortions such as rotation, viewpoint angle or lighting condition. In this work, new insights are discovered about CNN embeddings and a new loss function is proposed, derived from the contrastive loss, that creates models with more predicable mappings and also quantifies distortions. In typical distortion-dependent methods, there is no simple relation between the features corresponding to one image and the features of this image distorted. Therefore, these methods require to feed-forward inputs under every distortions in order to find the corresponding features representations. Our contribution makes a step towards embeddings where features of distorted inputs are related and can be derived from each others by the intensity of the distortion.
On non-canonical solving the Satisfiability problem
Venue: arXiv cs.DS 2015
Year: 2015

We study the non-canonical method for solving the Satisfiability problem which given by a formula in the form of the conjunctive normal form. The essence of this method consists in counting the number of tuples of Boolean variables, on which at least one clause of the given formula is false. On this basis the solution of the problem obtains in the form YES or NO without constructing tuple, when the answer is YES. It is found that if the clause in the given formula has pairwise contrary literals, then the problem can be solved efficiently. However, when in the formula there are a long chain of clauses with pairwise non-contrary literals, the solution leads to an exponential calculations.
An Analytic Framework for Maritime Situation Analysis
Venue: arXiv cs.LG 2015
Year: 2015

Maritime domain awareness is critical for protecting sea lanes, ports, harbors, offshore structures and critical infrastructures against common threats and illegal activities. Limited surveillance resources constrain maritime domain awareness and compromise full security coverage at all times. This situation calls for innovative intelligent systems for interactive situation analysis to assist marine authorities and security personal in their routine surveillance operations. In this article, we propose a novel situation analysis framework to analyze marine traffic data and differentiate various scenarios of vessel engagement for the purpose of detecting anomalies of interest for marine vessels that operate over some period of time in relative proximity to each other. The proposed framework views vessel behavior as probabilistic processes and uses machine learning to model common vessel interaction patterns. We represent patterns of interest as left-to-right Hidden Markov Models and classify such patterns using Support Vector Machines.
Dictionary and Image Recovery from Incomplete and Random Measurements
Venue: arXiv cs.CV 2015
Year: 2015

This paper tackles algorithmic and theoretical aspects of dictionary learning from incomplete and random block-wise image measurements and the performance of the adaptive dictionary for sparse image recovery. This problem is related to blind compressed sensing in which the sparsifying dictionary or basis is viewed as an unknown variable and subject to estimation during sparse recovery. However, unlike existing guarantees for a successful blind compressed sensing, our results do not rely on additional structural constraints on the learned dictionary or the measured signal. In particular, we rely on the spatial diversity of compressive measurements to guarantee that the solution is unique with a high probability. Moreover, our distinguishing goal is to measure and reduce the estimation error with respect to the ideal dictionary that is based on the complete image. Using recent results from random matrix theory, we show that applying a slightly modified dictionary learning algorithm over compressive measurements results in accurate estimation of the ideal dictionary for large-scale images. Empirically, we experiment with both space-invariant and space-varying sensing matrices and demonstrate the critical role of spatial diversity in measurements. Simulation results confirm that the presented algorithm outperforms the typical non-adaptive sparse recovery based on offline-learned universal dictionaries.
Local Color Contrastive Descriptor for Image Classification
Venue: arXiv cs.CV 2015
Year: 2015

Image representation and classification are two fundamental tasks towards multimedia content retrieval and understanding. The idea that shape and texture information (e.g. edge or orientation) are the key features for visual representation is ingrained and dominated in current multimedia and computer vision communities. A number of low-level features have been proposed by computing local gradients (e.g. SIFT, LBP and HOG), and have achieved great successes on numerous multimedia applications. In this paper, we present a simple yet efficient local descriptor for image classification, referred as Local Color Contrastive Descriptor (LCCD), by leveraging the neural mechanisms of color contrast. The idea originates from the observation in neural science that color and shape information are linked inextricably in visual cortical processing. The color contrast yields key information for visual color perception and provides strong linkage between color and shape. We propose a novel contrastive mechanism to compute the color contrast in both spatial location and multiple channels. The color contrast is computed by measuring \emph{f}-divergence between the color distributions of two regions. Our descriptor enriches local image representation with both color and contrast information. We verified experimentally that it can compensate strongly for the shape based descriptor (e.g. SIFT), while keeping computationally simple. Extensive experimental results on image classification show that our descriptor improves the performance of SIFT substantially by combinations, and achieves the state-of-the-art performance on three challenging benchmark datasets. It improves recent Deep Learning model (DeCAF) [1] largely from the accuracy of 40.94% to 49.68% in the large scale SUN397 database. Codes for the LCCD will be available.
Green Sensing and Access: Energy-Throughput Tradeoffs in Cognitive Networking
Venue: arXiv cs.IT 2015
Year: 2015

Limited spectrum resources and dramatic growth of high data rate applications have motivated opportunistic spectrum access utilizing the promising concept of cognitive networks. Although this concept has emerged primarily to enhance spectrum utilization and to allow the coexistence of heterogeneous network technologies, the importance of energy consumption imposes additional challenges, because energy consumption and communication performance can be at odds. In this paper, the approaches for energy efficient spectrum sensing and spectrum handoff, fundamental building blocks of cognitive networks is investigated. The tradeoff between energy consumption and throughput, under local as well as under cooperative sensing are characterized, and what further aspects need to be investigated to achieve energy efficient cognitive operation under various application requirements are discussed.
Noncommutative Valiant's Classes: Structure and Complete Problems
Venue: arXiv cs.CC 2015
Year: 2015

In this paper we explore the noncommutative analogues, $\mathrm{VP}_{nc}$ and $\mathrm{VNP}_{nc}$, of Valiant's algebraic complexity classes and show some striking connections to classical formal language theory. Our main results are the following: (1) We show that Dyck polynomials (defined from the Dyck languages of formal language theory) are complete for the class $\mathrm{VP}_{nc}$ under $\le_{abp}$ reductions. Likewise, it turns out that $\mathrm{PAL}$ (Palindrome polynomials defined from palindromes) are complete for the class $\mathrm{VSKEW}_{nc}$ (defined by polynomial-size skew circuits) under $\le_{abp}$ reductions. The proof of these results is by suitably adapting the classical Chomsky-Schützenberger theorem showing that Dyck languages are the hardest CFLs. (2) Next, we consider the class $\mathrm{VNP}_{nc}$. It is known~\cite{HWY10a} that, assuming the sum-of-squares conjecture, the noncommutative polynomial $\sum_{w\in\{x_0,x_1\}^n}ww$ requires exponential size circuits. We unconditionally show that $\sum_{w\in\{x_0,x_1\}^n}ww$ is not $\mathrm{VNP}_{nc}$-complete under the projection reducibility. As a consequence, assuming the sum-of-squares conjecture, we exhibit a strictly infinite hierarchy of p-families under projections inside $\mathrm{VNP}_{nc}$ (analogous to Ladner's theorem~\cite{Ladner75}). In the final section we discuss some new $\mathrm{VNP}_{nc}$-complete problems under $\le_{abp}$-reductions. (3) Inside $\mathrm{VP}_{nc}$ too we show there is a strict hierarchy of p-families (based on the nesting depth of Dyck polynomials) under the $\le_{abp}$ reducibility.